Global hotspots where breast cancer and atrial fibrillation overlap

By Dr. Priyom Bose, Ph.D.Reviewed by Lauren HardakerJul 10 2026

A global analysis of women aged 55 and older reveals where breast cancer and atrial fibrillation most closely overlap, highlighting smoking and alcohol use as shared modifiable risk factors that could inform more targeted prevention strategies.

Study: Global Geospatial Trends in Breast Cancer and Atrial Fibrillation/Flutter Among Older Women: Uncovering Shared Epidemiological Patterns and Etiological Links. Image credit: Bored Photography/Shutterstock.com

A recent study in the Journal of the American Heart Association mapped global geospatial patterns and hotspots of breast cancer (BC) and atrial fibrillation/flutter (AF) incidence overlap in women aged 55 and older, and examined shared epidemiological features and possible etiological connections between the two conditions.

Overlooked intersection of breast cancer and atrial fibrillation

Breast cancer (BC) remains a leading malignancy among women worldwide, marked by high incidence and mortality. Incidence rates are greater in developed regions, while areas with lower incidence, such as parts of Asia and Africa, often face disproportionate mortality.

Major BC risk factors include genetic predisposition (such as BRCA1/2 mutations), hormonal and reproductive history, obesity, alcohol use, and physical inactivity. Preventive efforts primarily target modifiable lifestyle factors and advocate for early detection. Notably, an estimated quarter of BC cases could be prevented by addressing alcohol consumption, obesity, and hormone use, although this estimate is based primarily on evidence from high-income countries.

Atrial fibrillation (AF) is the most common cardiac arrhythmia, impacting 2–4% of the global population, with prevalence increasing alongside life expectancy. AF frequently co-occurs with BC and shares risk factors such as aging, obesity, metabolic syndrome, and alcohol use, compounding the burden of both conditions.

Epidemiological evidence shows a bidirectional association: AF risk rises after BC diagnosis, and people with BC have higher AF incidence, and vice versa. Both disorders are strongly age-dependent, with BC incidence climbing post-menopause and AF risk rising exponentially with age. Accordingly, the combined burden of BC and AF in women aged 55 and older is rapidly intensifying with global population aging.

Despite this, most research focuses on single-disease analyses, leaving a significant gap regarding their overlapping geographic patterns and shared population-level risk factors. The lack of integrated studies on spatial patterns and region-specific risk factors for both diseases highlights the urgent need for comprehensive approaches to address this dual public health challenge.

Assessing spatial patterns and risk factors

A unified analytical framework was developed to integrate BC and AF analysis using Global Burden of Disease (GBD) 2021 data, focusing on women aged 55 and older across 204 countries and territories. This dataset, covering 369 diseases and 87 risk factors, enabled mapping of national patterns of disease incidence overlap and the identification of spatial targets for precision prevention.

Disease burden was classified by incidence quartiles, with countries grouped as consistent, AF-dominant, or BC-dominant to highlight spatial patterns. "Consistent" countries were those where BC and AF fell within the same incidence quartile, whereas BC- and AF-dominant countries had a higher quartile for one disease than the other. Machine learning techniques, including random forest and SHAP (Shapley Additive Explanations), were used to identify and rank key candidate risk factors, while population-attributable fractions (PAF) quantified their potential impact.

After excluding ineligible variables, 37 out of 58 risk factors were analyzed. Double Machine Learning was then applied to estimate potential causal associations at the population level, using separate models for BC and AF because the country-level data could not identify women with both conditions.

Multi-region assessment demonstrates correlation and modifiable risks in BC and AF

This study mapped the global incidence rates of BC and AF among women aged 55 and older across 202 countries, excluding Tuvalu and Tokelau due to limited data. Incidence rates showed geographic overlap, with higher rates in Europe, North America, and Oceania, and lower rates in southern and eastern regions. Certain countries in Oceania, Southeast Asia, and South America displayed elevated AF incidence.

Positive correlations between BC and AF incidence were observed across all regional classifications, although the relationship was strongest in consistent regions and weakest in AF-dominant regions.

Three incidence patterns emerged: countries where BC and AF fell within the same incidence quartile ("consistent" regions); BC-dominant regions, mainly in Asia and northern South America; and AF-dominant regions, found in parts of Africa and southern South America. The highest incidence rates for both diseases were concentrated in North America, Europe, and Oceania, while the lowest occurred in Northern and Central Africa. Each country demonstrated a distinct profile of incidence and risk-factor exposure.

The study assessed 58 possible risk factors, narrowing the initial machine-learning screening to eight key candidate risks for each disease. For BC, key factors included sugar-sweetened beverages, smoking, alcohol, high BMI, low physical activity, red meat, high plasma glucose, and low whole grain intake. For AF, the main risks were high sodium, smoking, alcohol, processed meat, radon, high LDL cholesterol, sugar-sweetened beverages, and red meat.

Four main risk factors showed significant associations in the subsequent Double Machine Learning analysis: smoking and alcohol (common to both diseases), and high BMI and low physical activity (specific to BC). Alcohol emerged as the strongest risk factor, with a one-standard-deviation increase in standardized exposure associated with up to a 12% higher BC incidence and a 10% higher AF incidence. Population-attributable fraction modeling estimated that shifting these exposures to their theoretical minimum-risk levels could reduce BC by 29% and AF by nearly 12%, particularly in regions where both diseases overlap.

Western, Northern, and Southern regions, particularly North America and Oceania, had the highest smoking and alcohol exposure levels. The United States, Canada, and Australia were among the countries with high exposure to both smoking and alcohol, while Australia and Luxembourg recorded particularly high alcohol exposure. High BMI was most prevalent in the Pacific Islands and the Middle East, including Kuwait, Jordan, and Qatar, whereas low physical activity was highest in locations such as the Marshall Islands, American Samoa, and Qatar. These trends underscore the influence of metabolic and lifestyle factors in BC and the necessity for targeted interventions.

A composite exposure index, ranging from 0 to 11, indicated the highest cumulative risk-factor exposure in Europe, Oceania, South America, and the United States, and the lowest in Africa and parts of Asia. This pattern closely aligned with BC and AF incidence rates.

Although countries demonstrated unique risk profiles, overlap between BC and AF risk factors was common. Exposure remained lowest in parts of Africa and South Asia and highest in Poland, Iceland, Monaco, Australia, New Zealand, Argentina, and the United States. Addressing both shared and disease-specific risks is essential to reducing the global burden of BC and AF.

Integrated prevention could address two major health burdens

The current study highlights the importance of integrated approaches for addressing BC and AF as global health conditions with overlapping geographic patterns and shared population-level risk factors.

Combining insights from spatial epidemiology, machine learning, and clinical research enables a deeper understanding of how these diseases may share common population-level drivers, although the ecological design cannot establish individual-level causality or confirm that women with one condition developed the other.

Continued research, especially with diverse data sources and a broader set of risk factors, will be essential for refining prevention strategies and enhancing patient outcomes. The authors also note that differences in disease reporting and diagnosis across countries may have influenced the incidence estimates, particularly in lower-resource settings.

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